修正负SEA损失因子的蒙特卡罗滤波方法

IF 1.3 Q3 ACOUSTICS
Paweł Nieradka, A. Dobrucki
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引用次数: 0

摘要

蒙特卡罗滤波(MCF)是实验统计能量分析(E-SEA)的一种方法,它允许对负LFs(损耗因子)进行校正。本文提出了一种改进的MCF方法,称为DESA(对角扩展搜索区域)。该技术在生成归一化能量矩阵的种群时应用了搜索区域的非均匀扩展。搜索区域的扩展程度由对角惩罚因子(DPF)控制。作者证明了该方法在经典MCF方法无法在多个频带中识别的系统上的有效性。应用DESA后,可以填充缺失CLF(耦合损耗因子)和DLF(阻尼损耗因子)值的问题带。本文还提出了一种减小由于使用过高的DPF值所带来的误差的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Modification of the Monte Carlo Filtering Approach for Correcting Negative SEA Loss Factors
Monte Carlo Filtering (MCF) is one of the methods of Experimental Statistical Energy Analysis (E-SEA), which allows the correction of negative LFs (Loss Factors). In this article, a modification of the MCF method, called DESA (Diagonal Expansion of the Search Area), is proposed. The technique applies a non-uniform extension of the search area when generating a population of normalized energy matrices. The degree of expansion of the search area is controlled by the Diagonal Penalty Factor (DPF). The authors demonstrated the method’s effectiveness on a system that could not be identified in several frequency bands by the classical MCF method. After applying DESA, it was possible to fill in the problematic bands that were missing CLF (coupling loss factor) and DLF (damping loss factor) values. The paper also proposes a way to minimize the errors introduced by using overly high DPF values.
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来源期刊
CiteScore
3.70
自引率
0.00%
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审稿时长
11 weeks
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